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Such a relationship between the response variable and explanatory variables is called a profile.
Second Order Response Surface Designs (SORDs) are used to explore relationship between the response variable and the input variables and to find out the optimum input combinations to achieve a desired response.
Multiple linear regression shows the relationship between the response variable and at least two predictor variables by fitting a linear equation to the observed data points.
MLR is performed either to study the relationship between the response variable and predictor variables or to predict the response variable based on the predictor variables.
A regression model is a compact mathematical representation of the relationship between the response variable and the input parameters in a given design space.
It was observed from the results that SRSM model is efficient for analyzing the stochastic relation between the response variable and uncertain explanatory variables.
Similar(27)
Quantitative loading structure performance maps are developed between the response variables and structural and load attributes.
The response surfaces between the response variables, i.e. crystallite size, lattice strain of the aluminum matrix and the processing parameters are presented.
Furthermore, in many situations the relationship between the response variables and design variables is too complex to be efficiently estimated using traditional surface fitting approaches.
In some real cases, more complicated models such as multivariate profile, rather than simple linear profile is addressed to model the performance of the process because of the existence of correlation between the response variables.
CCA takes advantage of the correlations between the response variables to improve predictive accuracy [40].
More suggestions(18)
between the response patterns
between the explanatory variable
between the entrepreneurship variable
between the forest variable
between the fluid variable
between the exposure variable
between the damage variable
between the partner variable
between the generation variable
between the education variable
between the control variable
between the predictor variable
between the feature variable
between the outcome variable
between the response current
between the health variable
between the input variable
between the target variable
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